{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上一篇Notebook演示了如何在线获取数据，主要用到的函数是：QA_fetch_get_xxx系列\n",
    "\n",
    "当然一般策略构建的时候，我们主要考虑的是从本地获取数据并进行分析，于是这篇Notebook将告诉你如何使用QA_fetch_xxx_adv系列"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这篇Notebook用来演示QA在pd.DataFrame的基础上封装的DataStruct数据结构。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import QUANTAXIS as QA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### save金融数据到本地数据库"
   ]
  },
  {
   "attachments": {
    "%E5%9B%BE%E7%89%87.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "当你能成功引入最新版本QA包的时候，意味着你已经安装好了各种依赖包，并且本地开启了mongodb数据库，QA可以很方便的一键存储常用的金融数据到本地，你只需要在terminal输入QUANTAXIS，然后输入save,就会出现如下提示框，输入对应命令保存数据即可。\n",
    "\n",
    "![%E5%9B%BE%E7%89%87.png](attachment:%E5%9B%BE%E7%89%87.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 通过数据库获取数据\n",
    "\n",
    "**通过本地数据库获取数据的方法为QA_fetch_xxx_adv系列**\n",
    "\n",
    "接下来我们将演示如何通过数据库获取多个股票的日线[\"000001\",'000002','000004']\n",
    "\n",
    "如果你还没有保存数据可以尝试使用save stock_day命令保存所有股票日线,大概1G的数据。也可以尝试使用save single_stock_day 000001这样的命令把我们要演示的三个股票数据快速保存。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'QUANTAXIS.QAData.QADataStruct.QA_DataStruct_Stock_day'>\n",
      "< QA_DataStruct_Stock_day with 3 securities >\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "通过本地数据库获取股票日线数据：\n",
    "QA.QA_fetch_stock_day_adv(\n",
    "    code,\n",
    "    start='all',\n",
    "    end=None,\n",
    "    if_drop_index=True,\n",
    "    collections=Collection(Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'quantaxis'), 'stock_day'),\n",
    ")\n",
    "\"\"\"\n",
    "\n",
    "data=QA.QA_fetch_stock_day_adv([\"000001\",'000002','000004'],'2017-01-01','2017-11-30')\n",
    "\n",
    "print(type(data)) # 得到的数据是在pd.DataFrame的基础上封装的DataStruct数据结构，比df多了很多特性和方法（接下来会演示\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
       "      <th>preclose</th>\n",
       "      <th>adj</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-03</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.11</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.16</td>\n",
       "      <td>459840.0</td>\n",
       "      <td>420595168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.55</td>\n",
       "      <td>20.88</td>\n",
       "      <td>20.55</td>\n",
       "      <td>20.73</td>\n",
       "      <td>217016.0</td>\n",
       "      <td>449757472.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.81</td>\n",
       "      <td>44.84</td>\n",
       "      <td>43.61</td>\n",
       "      <td>44.45</td>\n",
       "      <td>7154.0</td>\n",
       "      <td>31737710.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-04</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.15</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.14</td>\n",
       "      <td>9.16</td>\n",
       "      <td>449329.0</td>\n",
       "      <td>411503456.0</td>\n",
       "      <td>9.16</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.74</td>\n",
       "      <td>20.95</td>\n",
       "      <td>20.45</td>\n",
       "      <td>20.85</td>\n",
       "      <td>331554.0</td>\n",
       "      <td>686745344.0</td>\n",
       "      <td>20.73</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.43</td>\n",
       "      <td>44.82</td>\n",
       "      <td>44.01</td>\n",
       "      <td>44.70</td>\n",
       "      <td>8719.0</td>\n",
       "      <td>38703388.0</td>\n",
       "      <td>44.45</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close    volume       amount  \\\n",
       "date       code                                                        \n",
       "2017-01-03 000001   9.11   9.18   9.09   9.16  459840.0  420595168.0   \n",
       "           000002  20.55  20.88  20.55  20.73  217016.0  449757472.0   \n",
       "           000004  44.81  44.84  43.61  44.45    7154.0   31737710.0   \n",
       "2017-01-04 000001   9.15   9.18   9.14   9.16  449329.0  411503456.0   \n",
       "           000002  20.74  20.95  20.45  20.85  331554.0  686745344.0   \n",
       "           000004  44.43  44.82  44.01  44.70    8719.0   38703388.0   \n",
       "\n",
       "                   preclose  adj  \n",
       "date       code                   \n",
       "2017-01-03 000001       NaN  1.0  \n",
       "           000002       NaN  1.0  \n",
       "           000004       NaN  1.0  \n",
       "2017-01-04 000001      9.16  1.0  \n",
       "           000002     20.73  1.0  \n",
       "           000004     44.45  1.0  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 也可以使用.data来获取我们熟悉的pd.DataFrame形式\n",
    "df=data.data\n",
    "print(type(df))\n",
    "df.head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-01-03', '2017-01-04', '2017-01-05', '2017-01-06',\n",
       "               '2017-01-09', '2017-01-10', '2017-01-11', '2017-01-12',\n",
       "               '2017-01-13', '2017-01-16',\n",
       "               ...\n",
       "               '2017-11-17', '2017-11-20', '2017-11-21', '2017-11-22',\n",
       "               '2017-11-23', '2017-11-24', '2017-11-27', '2017-11-28',\n",
       "               '2017-11-29', '2017-11-30'],\n",
       "              dtype='datetime64[ns]', name='date', length=223, freq=None)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 多股票pd获取不重复index的方法\n",
    "df.index.levels[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['000001', '000002', '000004'], dtype='object', name='code')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 可以直接使用DataStruct来获得需要的值\n",
    "\n",
    "data.open\n",
    "data.close\n",
    "data.high\n",
    "data.low\n",
    "data.date # df.date没有\n",
    "data.datetime # df.datetime没有\n",
    "data.code #df.code没有"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QUANTAXIS>> none support type for qfq Current type is: qfq\n"
     ]
    }
   ],
   "source": [
    "# 使用DataStruct可以批量对股票数据进行复权处理\n",
    "\n",
    "#data=data.to_hfq() # 批量后复权\n",
    "data=data.to_qfq() # 批量前复权"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看数据\n",
    "DataStruct有三种方式可以查看数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t1=data.show() #log太长就不演示打印了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-03</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.11</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.16</td>\n",
       "      <td>459840.0</td>\n",
       "      <td>420595168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.55</td>\n",
       "      <td>20.88</td>\n",
       "      <td>20.55</td>\n",
       "      <td>20.73</td>\n",
       "      <td>217016.0</td>\n",
       "      <td>449757472.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.81</td>\n",
       "      <td>44.84</td>\n",
       "      <td>43.61</td>\n",
       "      <td>44.45</td>\n",
       "      <td>7154.0</td>\n",
       "      <td>31737710.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-04</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.15</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.14</td>\n",
       "      <td>9.16</td>\n",
       "      <td>449329.0</td>\n",
       "      <td>411503456.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.74</td>\n",
       "      <td>20.95</td>\n",
       "      <td>20.45</td>\n",
       "      <td>20.85</td>\n",
       "      <td>331554.0</td>\n",
       "      <td>686745344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.43</td>\n",
       "      <td>44.82</td>\n",
       "      <td>44.01</td>\n",
       "      <td>44.70</td>\n",
       "      <td>8719.0</td>\n",
       "      <td>38703388.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close    volume       amount\n",
       "date       code                                                     \n",
       "2017-01-03 000001   9.11   9.18   9.09   9.16  459840.0  420595168.0\n",
       "           000002  20.55  20.88  20.55  20.73  217016.0  449757472.0\n",
       "           000004  44.81  44.84  43.61  44.45    7154.0   31737710.0\n",
       "2017-01-04 000001   9.15   9.18   9.14   9.16  449329.0  411503456.0\n",
       "           000002  20.74  20.95  20.45  20.85  331554.0  686745344.0\n",
       "           000004  44.43  44.82  44.01  44.70    8719.0   38703388.0"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2=data() #推荐直接使用()的方式查看数据 这个数据是Pandas.Dataframe格式\n",
    "t2.head(6) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-03</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.11</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.16</td>\n",
       "      <td>459840.0</td>\n",
       "      <td>420595168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.55</td>\n",
       "      <td>20.88</td>\n",
       "      <td>20.55</td>\n",
       "      <td>20.73</td>\n",
       "      <td>217016.0</td>\n",
       "      <td>449757472.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.81</td>\n",
       "      <td>44.84</td>\n",
       "      <td>43.61</td>\n",
       "      <td>44.45</td>\n",
       "      <td>7154.0</td>\n",
       "      <td>31737710.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-04</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.15</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.14</td>\n",
       "      <td>9.16</td>\n",
       "      <td>449329.0</td>\n",
       "      <td>411503456.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.74</td>\n",
       "      <td>20.95</td>\n",
       "      <td>20.45</td>\n",
       "      <td>20.85</td>\n",
       "      <td>331554.0</td>\n",
       "      <td>686745344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.43</td>\n",
       "      <td>44.82</td>\n",
       "      <td>44.01</td>\n",
       "      <td>44.70</td>\n",
       "      <td>8719.0</td>\n",
       "      <td>38703388.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close    volume       amount\n",
       "date       code                                                     \n",
       "2017-01-03 000001   9.11   9.18   9.09   9.16  459840.0  420595168.0\n",
       "           000002  20.55  20.88  20.55  20.73  217016.0  449757472.0\n",
       "           000004  44.81  44.84  43.61  44.45    7154.0   31737710.0\n",
       "2017-01-04 000001   9.15   9.18   9.14   9.16  449329.0  411503456.0\n",
       "           000002  20.74  20.95  20.45  20.85  331554.0  686745344.0\n",
       "           000004  44.43  44.82  44.01  44.70    8719.0   38703388.0"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t3=data.data\n",
    "t3.head(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据查询 .query()\n",
    "DataStruct拥有很方便的数据查询功能，这也是对比df更好用的一个特性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-03</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.11</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.16</td>\n",
       "      <td>459840.0</td>\n",
       "      <td>420595168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.55</td>\n",
       "      <td>20.88</td>\n",
       "      <td>20.55</td>\n",
       "      <td>20.73</td>\n",
       "      <td>217016.0</td>\n",
       "      <td>449757472.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>44.81</td>\n",
       "      <td>44.84</td>\n",
       "      <td>43.61</td>\n",
       "      <td>44.45</td>\n",
       "      <td>7154.0</td>\n",
       "      <td>31737710.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close    volume       amount\n",
       "date       code                                                     \n",
       "2017-01-03 000001   9.11   9.18   9.09   9.16  459840.0  420595168.0\n",
       "           000002  20.55  20.88  20.55  20.73  217016.0  449757472.0\n",
       "           000004  44.81  44.84  43.61  44.45    7154.0   31737710.0"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查询日期\n",
    "data.query('date==\"2017-01-03\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
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       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.11</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.09</td>\n",
       "      <td>9.16</td>\n",
       "      <td>459840.0</td>\n",
       "      <td>420595168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.15</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.14</td>\n",
       "      <td>9.16</td>\n",
       "      <td>449329.0</td>\n",
       "      <td>411503456.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.17</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.15</td>\n",
       "      <td>9.17</td>\n",
       "      <td>344372.0</td>\n",
       "      <td>315769696.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   open  high   low  close    volume       amount\n",
       "date       code                                                  \n",
       "2017-01-03 000001  9.11  9.18  9.09   9.16  459840.0  420595168.0\n",
       "2017-01-04 000001  9.15  9.18  9.14   9.16  449329.0  411503456.0\n",
       "2017-01-05 000001  9.17  9.18  9.15   9.17  344372.0  315769696.0"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据筛选--选取某一只股票的数据 select_code\n",
    "data_000001=data.select_code('000001') #注意查询的结果还是DataStruct结构，要用()方法查看\n",
    "data_000001().head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-11</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.14</td>\n",
       "      <td>9.17</td>\n",
       "      <td>9.13</td>\n",
       "      <td>9.14</td>\n",
       "      <td>303430.0</td>\n",
       "      <td>277553216.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.52</td>\n",
       "      <td>20.63</td>\n",
       "      <td>20.40</td>\n",
       "      <td>20.40</td>\n",
       "      <td>168652.0</td>\n",
       "      <td>345421504.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>43.00</td>\n",
       "      <td>43.35</td>\n",
       "      <td>42.45</td>\n",
       "      <td>42.45</td>\n",
       "      <td>10668.0</td>\n",
       "      <td>45700196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2017-01-12</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.13</td>\n",
       "      <td>9.17</td>\n",
       "      <td>9.13</td>\n",
       "      <td>9.15</td>\n",
       "      <td>428006.0</td>\n",
       "      <td>391869408.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>42.10</td>\n",
       "      <td>42.78</td>\n",
       "      <td>42.04</td>\n",
       "      <td>42.05</td>\n",
       "      <td>7659.0</td>\n",
       "      <td>32499946.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-13</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.14</td>\n",
       "      <td>9.19</td>\n",
       "      <td>9.12</td>\n",
       "      <td>9.16</td>\n",
       "      <td>434301.0</td>\n",
       "      <td>397601920.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close    volume       amount\n",
       "date       code                                                     \n",
       "2017-01-11 000001   9.14   9.17   9.13   9.14  303430.0  277553216.0\n",
       "           000002  20.52  20.63  20.40  20.40  168652.0  345421504.0\n",
       "           000004  43.00  43.35  42.45  42.45   10668.0   45700196.0\n",
       "2017-01-12 000001   9.13   9.17   9.13   9.15  428006.0  391869408.0\n",
       "           000004  42.10  42.78  42.04  42.05    7659.0   32499946.0\n",
       "2017-01-13 000001   9.14   9.19   9.12   9.16  434301.0  397601920.0"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据筛选- 选取某一段时间内的数据\n",
    "res=data.select_time('2017-01-11','2017-01-31')\n",
    "res().head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-11-29</th>\n",
       "      <th>000001</th>\n",
       "      <td>13.73</td>\n",
       "      <td>13.93</td>\n",
       "      <td>13.47</td>\n",
       "      <td>13.82</td>\n",
       "      <td>1564094.0</td>\n",
       "      <td>2.148313e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>30.78</td>\n",
       "      <td>33.83</td>\n",
       "      <td>30.28</td>\n",
       "      <td>33.82</td>\n",
       "      <td>897712.0</td>\n",
       "      <td>2.894401e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>26.47</td>\n",
       "      <td>26.59</td>\n",
       "      <td>25.06</td>\n",
       "      <td>25.52</td>\n",
       "      <td>30904.0</td>\n",
       "      <td>7.867043e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-11-30</th>\n",
       "      <th>000001</th>\n",
       "      <td>13.70</td>\n",
       "      <td>13.73</td>\n",
       "      <td>13.26</td>\n",
       "      <td>13.38</td>\n",
       "      <td>1379635.0</td>\n",
       "      <td>1.866701e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>33.10</td>\n",
       "      <td>33.40</td>\n",
       "      <td>30.68</td>\n",
       "      <td>31.22</td>\n",
       "      <td>1000665.0</td>\n",
       "      <td>3.213854e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>25.50</td>\n",
       "      <td>25.82</td>\n",
       "      <td>25.16</td>\n",
       "      <td>25.56</td>\n",
       "      <td>23286.0</td>\n",
       "      <td>5.926307e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close     volume        amount\n",
       "date       code                                                       \n",
       "2017-11-29 000001  13.73  13.93  13.47  13.82  1564094.0  2.148313e+09\n",
       "           000002  30.78  33.83  30.28  33.82   897712.0  2.894401e+09\n",
       "           000004  26.47  26.59  25.06  25.52    30904.0  7.867043e+07\n",
       "2017-11-30 000001  13.70  13.73  13.26  13.38  1379635.0  1.866701e+09\n",
       "           000002  33.10  33.40  30.68  31.22  1000665.0  3.213854e+09\n",
       "           000004  25.50  25.82  25.16  25.56    23286.0  5.926307e+07"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 如果end设置为空,则获取到从start开始到最后的所有数据\n",
    "res=data.select_time('2017-11-11')\n",
    "res().tail(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-01-20</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.17</td>\n",
       "      <td>9.23</td>\n",
       "      <td>9.17</td>\n",
       "      <td>9.22</td>\n",
       "      <td>393328.0</td>\n",
       "      <td>361865152.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.60</td>\n",
       "      <td>20.83</td>\n",
       "      <td>20.54</td>\n",
       "      <td>20.68</td>\n",
       "      <td>215053.0</td>\n",
       "      <td>444921472.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>35.66</td>\n",
       "      <td>36.65</td>\n",
       "      <td>35.11</td>\n",
       "      <td>36.48</td>\n",
       "      <td>14226.0</td>\n",
       "      <td>51336036.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2017-01-23</th>\n",
       "      <th>000001</th>\n",
       "      <td>9.22</td>\n",
       "      <td>9.26</td>\n",
       "      <td>9.20</td>\n",
       "      <td>9.22</td>\n",
       "      <td>420299.0</td>\n",
       "      <td>388019072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>20.70</td>\n",
       "      <td>20.85</td>\n",
       "      <td>20.70</td>\n",
       "      <td>20.74</td>\n",
       "      <td>156373.0</td>\n",
       "      <td>324581600.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    open   high    low  close    volume       amount\n",
       "date       code                                                     \n",
       "2017-01-20 000001   9.17   9.23   9.17   9.22  393328.0  361865152.0\n",
       "           000002  20.60  20.83  20.54  20.68  215053.0  444921472.0\n",
       "           000004  35.66  36.65  35.11  36.48   14226.0   51336036.0\n",
       "2017-01-23 000001   9.22   9.26   9.20   9.22  420299.0  388019072.0\n",
       "           000002  20.70  20.85  20.70  20.74  156373.0  324581600.0"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据筛选 - 选取某一个时间点向前向后的数据\n",
    "# method\n",
    "# lt 小于 <\n",
    "# lte 小于等于  <=\n",
    "# gt 大于 >\n",
    "# gte 大于等于 >=\n",
    "# e 等于 ==\n",
    "res=data.select_time_with_gap(gap=5,method='lte',time='2017-01-31')\n",
    "res().head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "open            35.66\n",
       "high            36.65\n",
       "low             35.11\n",
       "close           36.48\n",
       "volume       14226.00\n",
       "amount    51336036.00\n",
       "Name: (2017-01-20 00:00:00, 000004), dtype: float64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据筛选 - 拿到某一天的股票数据\n",
    "# if_trade的作用是  如果if_trade=False 则遇到停牌时 会返回最后一个交易日的bar\n",
    "res=data.get_bar(code='000004',time='2017-01-20')\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>code</th>\n",
       "      <th>000001</th>\n",
       "      <th>000002</th>\n",
       "      <th>000004</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>9.11</td>\n",
       "      <td>20.55</td>\n",
       "      <td>44.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>9.15</td>\n",
       "      <td>20.74</td>\n",
       "      <td>44.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>9.17</td>\n",
       "      <td>20.85</td>\n",
       "      <td>44.52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "code        000001  000002  000004\n",
       "date                              \n",
       "2017-01-03    9.11   20.55   44.81\n",
       "2017-01-04    9.15   20.74   44.43\n",
       "2017-01-05    9.17   20.85   44.52"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据切面 pivot,\n",
    "\n",
    "res=data.pivot('open')\n",
    "print (type(res)) #得到的df类型\n",
    "res.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 快速计算指标*\n",
    "你可能需要对很多只股票同时计算指标，用DataStruct就可以非常方便的得到结果，要做的只不过是对数据块应用函数 add_func 就行了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>TR</th>\n",
       "      <th>ATR</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-11-29</th>\n",
       "      <th>000001</th>\n",
       "      <td>0.46</td>\n",
       "      <td>0.743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>3.55</td>\n",
       "      <td>1.890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>1.53</td>\n",
       "      <td>2.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2017-11-30</th>\n",
       "      <th>000001</th>\n",
       "      <td>0.56</td>\n",
       "      <td>0.754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>3.14</td>\n",
       "      <td>2.098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>0.66</td>\n",
       "      <td>2.158</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     TR    ATR\n",
       "date       code               \n",
       "2017-11-29 000001  0.46  0.743\n",
       "           000002  3.55  1.890\n",
       "           000004  1.53  2.420\n",
       "2017-11-30 000001  0.56  0.754\n",
       "           000002  3.14  2.098\n",
       "           000004  0.66  2.158"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 一般是配合指标函数去计算指标\n",
    "\n",
    "# QA.QA_indicator_ATR  ATR指标\n",
    "\n",
    "res=data.add_func(QA.QA_indicator_ATR,10)\n",
    "res.tail(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 格式转换 \n",
    "to_dict \n",
    "\n",
    "to_list\n",
    "\n",
    "to_numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "res=data.to_dict()\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res=data.to_list()\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res=data.to_numpy()\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 画图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QUANTAXIS>> The Pic has been saved to your path: ./QA_stock_day_000001_bfq.html\n",
      "QUANTAXIS>> The Pic has been saved to your path: ./QA_stock_day_None_bfq.html\n"
     ]
    }
   ],
   "source": [
    "data.plot('000001') #画某一只股票\n",
    "data.plot()  #画全部股票"
   ]
  }
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